1. Field of the Invention
The present invention generally relates to electrical, condition responsive systems. More particularly, this invention relates to a method and apparatus for detecting a fire in a monitored area.
2. Description of the Related Art
It is important that an optical fire detector be able to detect the presence of various types of flames in as reliable a manner as possible. This requires that a flame detector be able to discriminate between flames and other light sources. Commonly, such optical flame detection is carried out in the infrared (IR) portion of the light spectrum at around 4.5 microns, a wavelength that is characteristic of an emission peak for carbon dioxide.
Simple flame detectors employ a single sensor, and a warning is provided whenever the signal sensed by the detectors exceeds a particular threshold value. However, this simple approach suffers from false triggering, because it is unable to discriminate between flames and other bright objects, such as incandescent light bulbs, hot industrial processes such as welding, and sometimes even sunlight and warm hands waved in front of the detector.
Attempts have been made to overcome this problem by sensing radiation at two or more wavelengths. For example, see U.S. Pat. No. 5,625,342. Such comparisons of the relative strengths of the signals sensed at each wavelength have been found to permit greater discrimination regarding false sources than when sensing at only a single wavelength. However, such detectors can still be subject to high rates of false alarms.
Another technique for minimizing the occurrence of such false alarms is to use flicker detection circuitry which monitors radiation intensity variations over time, and thereby discriminate between a flickering flame source and a relatively constant intensity source such as a hot object.
Meanwhile, U.S. Pat. No. 5,510,772 attempts to minimize such false fire alarms by using a camera operating in the near infrared range to capture a succession of images of the space to be monitored. The brightness or intensity of the pixels comprising these images is converted to a binary value by comparing it with the average intensity value for the image (e.g., 1 if greater than the average). Computing for each pixel a crossing frequency, v (defined as the number of times that its binary value changes divided by the II number of images captured) and an average pixel binary value, C (defined as the average over all the images for a specific pixel). Testing the values of v and C against the relationship: v=KC(1-C), where K is a constant; and signaling the existence of a fire for any cluster of adjacent pixels for which the respective values of v and C fit this relationship within predetermined limits.
Despite such improvement efforts, these fire detectors can still be subject to high rates of false alarms, and misdiagnosis of true fires. For example, there can still be significant difficulties in producing true alarms when monitoring fires at a long distance from the detector, say up to approximately two hundred feet, when the signal to noise ratio is small. This may present even higher challenge when other active or passive light sources are present, such as spot welding, reflecting surfaces of water, flickering luminescent light fixtures etc.
Also, fire detectors suffer from an inconsistency in fire detection characteristics under different fire conditions, such as with different levels of fire temperature, size, position relative to the detector, fuel and interfering background radiation. Additionally, such detectors have little ability to pinpoint the exact location of a fire in a monitored area; information which can greatly aid the effective use of installed suppression systems. Consequently, there is still a need for a fire detector with exact fire location capabilities and whose ability to detect fires is less dependent on the various factors listed above.